A depression is a sunken area on Earth's surface surrounded by higher ground in all directions. Surface depressions are bowl-like landforms across a range of spatial scales. They are formed by either natural or anthropogenic processes. Natural surface depressions are abundant in topographically complex landscapes, particularly in glaciated, Karst, volcanic or Aeolian landscapes (e.g. Huang, et al. “Differentiating tower karst (fenglin) and cockpit karst (fengcong) using DEM contour, slope, and centroid,” Environmental Earth Sciences, 72(2), 407-416 (2014), the entire disclosure of which is incorporated herein by this reference).
Examples of natural depressions include glaciated kettle lakes, cirques, prairie potholes, Karst sinkholes, volcanic craters, pit craters, impact craters, etc. Some surface depressions are related to a variety of human activities, such as, constructing detention basins and reservoirs, mining, quarrying, charcoal or lime production, or bombing.
Surface depressions trap, collect and often hold overland runoff from higher areas of their closed interior drainage basins during rainfall events and snowmelt in the spring. Therefore, they are often covered by water temporarily, seasonally or permanently, forming ponds, lakes, or wetland landscapes. Depressions trap and store sediment and nutrients, enhance water loss to the atmosphere via evaporation and to deep groundwater via infiltration, and provide critical habitats for plants and animals, having profound impacts on local or regional hydrologic, ecologic, and biogeochemical processes. The existence and density of surface depressions control hydrological partitioning of rainfall into infiltration and runoff and hydrologic connectivity, influence soil moisture states and vegetation patterns, regulate runoff water quality through trapping and filtering pollutants, wastes, sediments and excess nutrients, and create the wet and nutrient-rich environmental conditions for many species to exist and reproduce. The vital hydrologic and ecologic effects of surface depressions are largely determined by their geographical location, surface area, depth, storage volume, geometric shape, and other properties. Some of these properties are changing over time due to sedimentation, erosion, vegetation dynamics, and other processes. Detection, delineation and quantitative characterization of surface depressions with accurate and up-to-date information are critical to many scientific studies and practical applications, such as ecohydrologic modeling, limnological analyses, and wetland conservation and management.
However, most previous studies were based on coarse resolution topographical data, in which surface depressions are treated as nuisance or spurious features. This is because coarse resolution topographic data are unable to reliably resolve small surface depressions and the noise and error in the topographic data tend to create artifact depressions, which are difficult to distinguish from real surface depression features. In a standard hydrological analysis, surface depressions are identified and then simply removed to create a depressionless surface topography, which ensures that water flows continuously across the topographic surface to the watershed outlets and that the derived stream networks are fully connected for runoff routing. Depressions are typically removed by raising the elevations in depressions with a depression-filling algorithm, or less commonly by lowering the elevations of the depression boundary with a depression-breaching algorithm. In the previous studies, little attention has been paid to the geometric and topological properties of surface depressions themselves, and the effects of surface depressions on local and regional hydrology and ecology were largely ignored.
In recent decades, the advent of airborne light detection and ranging (LiDAR) and interferometric synthetic aperture radar (InSAR) remote sensing technologies have produced large volumes of highly accurate and densely sampled topographical measurements (1-5 m spatial resolution) (see White, S. A. et al. “Utilizing DEMs derived from LIDAR data to analyze morphologic change in the North Carolina coastline” Remote sensing of environment, (2003) 85(1), 39-47, and Finkl, et al. “Interpretation of seabed geomorphology based on spatial analysis of high-density airborne laser bathymetry” Journal of Coastal Research, (2005) 21(3), 501-514, the entire disclosures of which are incorporated herein by this reference). The increasing availability of high-resolution topographical data allows for an entirely new level of detailed delineation and analyses of small-scale geomorphologic features and landscape structures at fine scales (Ussyschkin, V. et al. “Airborne Lidar: Advances in Discrete Return Technology for 3D Vegetation Mapping.” (2010) Remote Sensing, 3(3), 416-434, the entire disclosure of which is incorporated herein by this reference).
To fully exploit high resolution topographical data for scientific investigation of hydrologic and ecologic effects of surface depressions, new algorithms and methods are required to efficiently delineate, identify, and quantify surface depressions across scales.